Global hypomethylation as an MRD biomarker in esophageal and esophagogastric junction adenocarcinoma 

Global hypomethylation as an MRD biomarker in esophageal and esophagogastric junction adenocarcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Global hypomethylation as an MRD biomarker in esophageal and esophagogastric junction adenocarcinoma Elisa Boldrin, Maria Assunta Piano, Alice Volpato, Rita Alfieri, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5348931/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Esophageal and esophagogastric junction adenocarcinoma (EADC-EGJA) prognosis is poor, and Barrett’s esophagus has increased risk of developing tumor through the carcinogenesis process from metaplasia/low-grade dysplasia to high-grade dysplasia (HGD). Long interspersed nuclear element-1 (LINE-1) is considered a surrogate marker of global methylation, an epigenetic event contributing to progression. cfDNA of 90 patients with never dysplastic Barrett’s (NDBE), HGD/early EADC-EGJA or locally advanced/advanced EADC-EGJA have been analyzed for LINE-1 methylation, by Methylation-Sensitive Restriction Enzyme droplet digital PCR. Twenty-six patients have been longitudinally studied. Global hypomethylation increased during carcinogenesis, with significant difference between locally advanced/advanced EADC-EGJAs and NDBEs ( P = 0.028). Longitudinal cases confirmed rareness and stability over time of hypomethylation in NDBEs. The majority of HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA showed methylation dynamic after resection according to clinical status, suggesting that global hypomethylation occurs just prior to cancer invasiveness and it is a promising biomarker to monitor molecular residual disease/recurrence. esophageal adenocarcinoma (EADC) esophagogastric junction adenocarcinoma (EGJA) Barrett’s esophagus (BE) global hypomethylation liquid biopsy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Esophageal cancer (EC) is the 8th most commonly diagnosed cancer and the 6th most common cause of cancer death in the world 1 . In Europe, in 2020, EC accounted for about 52,993 new diagnoses and 45,551 deaths 2 . Although its burden varies greatly across countries and populations, due to differences in the prevalence of underlying risk factors, survival from EC remains low, in the range of 10–30% at 5 years post diagnosis in most countries 1 . Esophageal adenocarcinoma (EADC), the most frequent histotype of EC, occurs preferentially in the distal part of the esophagus, next to the junction with the stomach. Age, gender (male), smoking habit, persistent gastro-esophageal reflux disease (GERD) and obesity are all risk factors for EADC development 3 – 5 . The 8th edition of American Joint Committee on Cancer (AJCC) includes also the esophagogastric junction adenocarcinoma (EGJA) as EC when the tumor involves the junction and its epicenter is within the proximal 2 cm of the cardia 6 . At the histological level, it is recognized that Barrett’s esophagus (BE) is a risk condition for EADC and EGJA, indeed, the majority of EADC and EGJA cases arise in an area of BE 7 . BE is characterized by the substitution of normal esophageal epithelium with columnar epithelium. One of the major causes of this transformation is attributed to inflammation and cell proliferation induced by the chronic exposure of lower esophagus to acid and bile salts typical of GERD 8 . Indeed, BE prevalence is higher in the population with GERD (7.7%) compared with population without this condition (< 5%) 9 . BE could evolve to low-grade (LGD), high-grade dysplasia (HGD) and finally invasive EADC 10 . The risk of progression of BE to EADC is around 0.3% per year in absence of dysplasia, but the risk rises to 5–20% in presence of HGD 11 , 12 . These observations led to the activation of surveillance protocols based on repetitive endoscopies together with targeted biopsies of the suspected areas followed by random biopsy sampling of the entire BE segment 8 . Frequency of surveillance endoscopy is determined by the detection of dysplasia. However, the efficacy of current surveillance protocols is still a matter of debate, and there is a great need to find biomarkers that could help to identify those BE patients at risk of developing EADC, in order to better tailor their follow-up 8 . Moreover, there is still no consensus on indicators of EADC early detection, neither on monitoring of the duration of therapy response nor on early detection of progression/recurrence yet. At the molecular level, according to the multi-step model of progression, dysplasia evolves to invasive EADC via the progressive accumulation of mutations and somatic copy number alterations (SCNAs) in tumor suppressor genes and oncogenes 13 . Studies conducted by Next-generation sequencing (NGS) technologies revealed that also in never dysplastic Barrett’s esophagus (NDBE) are already present genetic alterations typical of EADC, suggesting that progression could be non-linear. These findings challenge the traditional multi-step model of progression to EADC 13 – 15 , and suggest that this progression is associated with a relatively small number of additional mutations or that other events are crucial to further promote the late step of carcinogenesis 16 . It has been proposed that one of the mechanisms that promote the rapid progression of preneoplastic lesions to invasive EADC is the occurrence of genomic catastrophes such as chromothripsis, repeated breakage–fusion–bridge cycles and whole-genome doubling (WGD) 16 . Growing evidence supports the hypothesis that epigenetic alterations can contribute to the acquisition of cancer hallmark capabilities during tumor development and malignant progression 17 . Among the possible epigenetic events, alteration of methylation level, primarily in the form of tumor suppressor gene hypermethylation, has been frequently found in EADC and NDBE 18 . Genome-wide methylation analysis conducted in a variety of cancers has revealed that, next to a selective hypermethylation at the CpG islands of specific tumor suppressor gene promoters, the dominant epigenetic change is global hypomethylation 19 , 20 . The Long-Interspersed Element-1 (LINE-1), since it constitutes a consistent part of the human genome (17%), has been indicated as a possible surrogate marker of global methylation status 21 , 22 . LINE-1 methylation analysis has been conducted in many of the most common lethal cancers, and has been often associated with a poor outcome 23 – 36 . In EC, LINE-1 status has been principally investigated in squamous cell carcinoma (ESCC), the other main EC histotype, in which its hypomethylation is frequent and associated with poorer survival 37 – 39 . In EADC there are less data, however, we have previously demonstrated that LINE-1 is frequently hypomethylated both in solid and liquid biopsies of EADC patients compared to the constitutive genomic DNA isolated from peripheral blood mononuclear cells (PBMCs) 40 . Other studies supported the occurrence of LINE-1 hypomethylation in EADC, such as the demonstration that its retrotransposition is active and contributes to its genomic instability through insertions in the coding sequence of several genes ( ERBB4 , CTNNA3 , CTNNA2 , CDH18 , and SOX5 ) 41 – 44 . Indeed, the retrotransposition of LINE-1 in cancer cells seems to be associated with its aberrant hypomethylation during carcinogenesis, while, in physiological conditions, retrotransposition is inhibited by hypermethylation of this element 45 . Due to these promising results in EADC, in this work, in order to define whether LINE-1 methylation level is affected during the carcinogenesis process, beside a cohort of 30 locally advanced/advanced EADC-EGJA patients, we extended the analysis, in liquid biopsy, of LINE-1 methylation status to HGD/early EADC-EGJA and to BE. Moreover, to define if this biomarker could predict the patient clinical outcome, for several individuals we included a longitudinal monitoring through repetitive cfDNA sampling. Considering the possibility to have a lower amount of cfDNA in the bloodstream of patients with pre-neoplastic lesions in comparison with those affected by tumor, the use of a sensitive molecular approach to improve LINE-1 methylation detection in liquid biopsy should be considered. To address this purpose, we choose droplet digital PCR (ddPCR) technology, which is an endpoint method for precise and absolute quantification of nucleic acids 46 . This feature, together with the partitioning of the sample in thousands of individual PCR reaction, offers the advantage of direct and accurate quantification of template, maximizing the chance to detect rare genetic alterations 47 . To discriminate methylated and unmethylated cytosines within CpG islands in LINE-1 promoter, a particular type of ddPCR called Methylation-Sensitive Restriction Enzyme ddPCR (MSRE-ddPCR) was used. Methods Patients In this prospective study, a total of 90 patients, 30 diagnosed with NDBE, 30 with HGD or early EADC-EGJA, and 30 with locally advanced/advanced EADC-EGJA have been included. NDBE were defined as BE patients with a clinical history of stable disease for at least 3 years (range: 3–12 years; median: 5 years). For NDBE patients, the length of the Barrett’s lesion defined the patient as “long” or “short” NDBE. All the enrolled patients were recruited from the Gastroenterology Unit and/or from the Surgical Oncology of Digestive Tract Unit of Veneto Institute of Oncology IOV – IRCCS (Padua, Italy) between July 2014 and June 2023. Inclusion criteria were: i) age > 18 years; ii) histological diagnosis of BE, HGD/early EADC-EGJA or locally advanced/advanced EADC-EGJA. Concurrent diagnosis of synchronous or metachronous tumor within 5 years was an exclusion criterium. For each patient, a blood sample was collected at different time points: at the enrollment for NDBEs, at the diagnosis/surgery for HGD/early EADC-EGJAs, and at the diagnosis/surgery for locally advanced/advanced EADC-EGJAs. Twenty-six of the 90 patients were also longitudinally studied including 11 NDBE, 7 HDG/early EADC-EGJA and 8 locally advanced/advanced EADC-EGJA patients. For these cases, at least two blood samples in different follow-up were collected. Blood samples of 20 healthy volunteers (median age: 30.5 years; range: 21–65 years; males: 8, females: 12) were also included. The present study was approved by the IOV-IRCCS Comitato Etico per la Sperimentazione Clinica (CESC) (cod. number CESC IOV: 2020/125) and carried out in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki and its later amendments). All the patients involved in this study expressed their written consensus to blood sampling and data treatment in accordance with the Helsinki Declaration. DNA extraction Peripheral blood samples were collected in cell-free DNA BCT tubes (Streck). Plasma was isolated as described in 48 . One aliquot of whole blood was also stored for germline DNA (gDNA) extraction. cfDNA was extracted from 1 ml of plasma using Maxwell RSC cfDNA Plasma Kit (Promega). gDNA was isolated from 500 µl of peripheral blood with Maxwell RSC Whole Blood DNA Kit (Promega). cfDNA and gDNA quantity were assessed with Qubit dsDNA HS Assay kit (Thermo Fisher Scientific). Quality of randomly selected cfDNA samples was evaluated by Agilent TapeStation 2200 using Cell-free DNA Screen Tape Assay kit (Agilent Technologies). Methylation-Sensitive Restriction Enzyme droplet digital PCR (MSRE-ddPCR) LINE-1 methylation was analyzed by a MSRE-ddPCR in-house designed assay. gDNA and cfDNA of each patient were digested or not digested with HpaII (New England BioLabs), a methylation-sensitive enzyme that cuts CCGG recognition site when both cytosines are unmethylated and, with a lower efficiency, when the external cytosine is methylated (mCCGG); while it is inhibited when both cytosines are methylated (mCmCGG). Digested and undigested DNA have been amplified by ddPCR with primers for the amplification of a sequence between nucleotides 12–128 of LINE-1 promoter (GenBank accession number X58075.1). This region contains two CCGG sites. Two different ddPCR reaction mixes of 20 µl with or without HpaII were prepared. Reaction mixes contained 10 µL of 2× ddPCR SuperMix for Probes (No dUTP) (Bio-Rad), 1 µL of 20× target LINE-1 primers/probe (FAM), 1 µL (10 U) of HpaII (for digested sample) or 1 µL of H 2 O (for undigested sample). The pair of primer/probe was in a final concentration of 900 nM/250 nM. Primer sequences were: 5′ -CAAGATGGCCGAATAGGAAC (FW) and 5′ -TGGCACTCCCTAGTGAGATG (RW). A DNA input of 0.01 ng/well was used as template. Each ddPCR included, as positive and negative controls, a Human WGA Methylated DNA and Human WGA Non-methylated DNA (Zymo Research). No-template control was included. Droplets were generated by QX200 droplet generator (Bio-Rad). An Applied Biosystems VeritiDx thermal cycler was used to perform first enzymatic digestion reaction at 37°C for 2 hours and, subsequently, enzyme inactivation at 95°C for 20’, followed by PCR amplification using these conditions: 95°C for 10′, followed by 50 cycles at 94°C for 30″, 60°C for 1′, and 98°C for 10′. Each reaction was performed in two replicates. Droplets were read with QX200 droplet reader and analyzed with QuantaSoft™ version 1.7.4 (Bio-Rad). Positive droplets, containing amplification products, were discriminated from negative ones by applying a fluorescence amplitude threshold that was set manually. The software quantified the number of copies/µL for each well as output. The mean of two replicates was calculated to obtain a more accurate value. Samples with < 10,000 droplets per 20 µL of PCR reaction were excluded from analysis. The methylation level in the cfDNA sample of a patient, using lymphocytes-derived gDNA as reference, was calculated by this formula: $$\:\mathbf{c}\mathbf{f}\mathbf{D}\mathbf{N}\mathbf{A}\:\mathbf{m}\mathbf{e}\mathbf{t}\mathbf{h}\mathbf{y}\mathbf{l}\mathbf{a}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n}\:\left(\mathbf{\%}\right)=\frac{\mathbf{n}^\circ\:\:\mathbf{c}\mathbf{o}\mathbf{p}\mathbf{i}\mathbf{e}\mathbf{s}/\varvec{\mu\:}\mathbf{L}\:\left(\mathbf{d}\mathbf{i}\mathbf{g}\mathbf{e}\mathbf{s}\mathbf{t}\mathbf{e}\mathbf{d}\:\mathbf{c}\mathbf{f}\mathbf{D}\mathbf{N}\mathbf{A}\right)\:)/\mathbf{n}^\circ\:\:\mathbf{c}\mathbf{o}\mathbf{p}\mathbf{i}\mathbf{e}\mathbf{s}/\varvec{\mu\:}\mathbf{L}(\mathbf{u}\mathbf{n}\mathbf{d}\mathbf{i}\mathbf{g}\mathbf{e}\mathbf{s}\mathbf{t}\mathbf{e}\mathbf{d}\:\mathbf{c}\mathbf{f}\mathbf{D}\mathbf{N}\mathbf{A})\:}{\mathbf{n}^\circ\:\:\mathbf{c}\mathbf{o}\mathbf{p}\mathbf{i}\mathbf{e}\mathbf{s}/\varvec{\mu\:}\mathbf{L}\left(\mathbf{d}\mathbf{i}\mathbf{g}\mathbf{e}\mathbf{s}\mathbf{t}\mathbf{e}\mathbf{d}\:\mathbf{g}\mathbf{D}\mathbf{N}\mathbf{A}\right)\:)/\mathbf{n}^\circ\:\:\mathbf{c}\mathbf{o}\mathbf{p}\mathbf{i}\mathbf{e}\mathbf{s}/\varvec{\mu\:}\mathbf{L}(\mathbf{u}\mathbf{n}\mathbf{d}\mathbf{i}\mathbf{g}\mathbf{e}\mathbf{s}\mathbf{t}\mathbf{e}\mathbf{d}\:\mathbf{g}\mathbf{D}\mathbf{N}\mathbf{A})\:}\varvec{x}\:100$$ To set up the cut-off value to consider a cfDNA as hypomethylated, we carried out the same procedure as the test samples by analyzing cfDNA and gDNA of 20 healthy volunteers. The established cut-off value, under which the test sample has been considered hypomethylated, was determined as the mean of the % methylation level of cfDNA − 2SD (98.67% − 2SD = 93.06%). Statistics Differences in distribution between groups for categorical variables were evaluated using chi-squared or Fisher’s exact test. Differences in distribution between groups for continuous variables were evaluated using Mann-Whitney or Kruskal-Wallis test. Correlation analysis was performed using Spearman’s test. Overall survival (OS) was defined as the time between the date of tumor resection and the date of death for any cause or the date of the end of study (January 2024). Progression-free survival (PFS) was calculated as the time from the date of tumor resection to the date of progression, or the date of the end of the study. OS and PFS curves were defined using Kaplan-Meier function, differences between strata were estimated using log-rank test. Tests with P values < 0.05 were considered statistically significant. Statistical analyses were performed using SigmaPlot version 14.0 (Systat Software Inc.). Graphs were generated using GraphPad Prism software (version 9.2 for Windows, San Diego, CA, USA). Results Clinicopathological characteristics of patients The clinicopathological characteristics of NDBE, HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA patients are reported in Table 1 . The median age is slightly lower in NDBE patients compared with HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA (54.5; 68 and 66; respectively). The male/female ratio is similar in the three cohorts with a prevalence of males. The majority of NDBE were long BE with the lesion located at the esophagus, HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA have the lesion/tumor located in the esophagus or esophageal junction. cStage and pStage were reported according to Rice et al. 6 . Only locally advanced/advanced EADC-EGJA received neoadjuvant treatment in almost all cases and received adjuvant therapy in case of pathological residual disease and suitability to receive the therapy. Table 1 Clinicopathological characteristics of NDBE, HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA. Patients NDBE HGD/early EADC-EGJA Locally adv./ adv. EADC-EGJA N (%) N (%) N (%) 30 (33.3%) 30 (33.3%) 30 (33.3%) Age Median (range) 54.5 (21–75) 68 (36–86) 66 (41–87) IQR 14.2 10.2 18 Gender Male 25 (83.3%) 27 (90%) 26 (86.7%) Female 5 (16.7%) 3 (10%) 4 (13.3%) Length of BE lesion Short (< 3 cm) 5 (16.67%) / / Long (≥ 3 cm) 25 (83.33%) / / Tumor site of lesion/tumor Esophagus 30 (100%) 26 (86.67%) 6 (20%) Esophageal junction 0 (0%) 4 (13.33%) 24 (80%) cStage 0 / 21 (70%) 0 (0%) I / 9 (30%) 0 (0%) III / 0 (0%) 22 (73.3%) IVA / 0 (0%) 3 (10%) IVB / 0 (0%) 2 (6.7%) Unknown / 0 (0%) 3 (10%) pStage 0 / 21 (70%) 3 (10%) I / 9 (30%) 0 (0%) IIB-IIIB / 0 (0%) 16 (53.3%) IVA / 0 (0%) 5 (16.7%) Unknown (no surgery) / 0 (0%) 6 (20%) Neoadjuvant treatment Yes / / 29 (96.7%) No / / 1 (3.3%) Adjuvant treatment Yes / / 12 (40%) No / / 18 (60%) NDBE: Never dysplastic Barrett; HGD: high-grade dysplasia; EADC: esophageal adenocarcinoma; EGJA: esophagogastric junction adenocarcinoma; IQR: interquartile range; BE: Barrett’s esophagus; cStage: clinical tumor stage; pStage: pathological tumor stage. LINE-1 Methylation analysis in cell-free DNA at baseline LINE-1 methylation level was analyzed by MSRE-ddPCR in all patients. A cfDNA sample was considered hypomethylated when its residual methylation level was below to the cut-off level of 93.06%, calculated by analyzing the cfDNA and the gDNA of 20 healthy volunteers. The distribution of the methylation level of the cfDNA samples in the three groups of patients is shown in Fig. 1 a. Three out of 30 (10%), 6 out of 30 (20%) and 10 out of 30 (33.3%) cfDNAs resulted hypomethylated in NDBE, HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA groups, respectively (Fig. 1 b). Locally advanced/advanced EADC-EGJAs had a significantly higher number of hypomethylated samples compared to NDBEs ( P = 0.028; Fig. 1 b), whereas the difference in the frequency of hypomethylated cfDNA samples was not significant between NDBEs and HGD/early EADC-EGJAs and between HGD/early EADC-EGJAs and locally advanced/advanced EADC-EGJAs (Fig. 1 b). The overall decrease of methylation level, considering all the hypomethylated samples of the three groups together, ranged from 7.6–20.8%, with a median of 11% (IQR = 5.9%). Association between LINE-1 methylation level and the clinicopathological characteristics of patients has been investigated. A correlation between LINE-1 methylation values and age in all patients considered together and divided by the three groups was not observed (r = 0.037, P = 0.727 for all patients; r = 0.073, P = 0.701 for NDBE; r = -0.078, P = 0.682 for HGD/early EADC-EGJA; r = 0.115, P = 0.546 for locally advanced/advanced EADC-EGJA). No correlation was observed for healthy controls either (r = -0.191, P = 0.419) (Fig. 2 ). Association between methylation level and gender in all patients has been not observed ( P = 0.112; Fig. 3 ). Concerning the preneoplastic lesion group (NDBE), association with the length of BE has not been found ( P = 0.69; Fig. 3 ). Moreover, in the two groups of neoplastic lesions (HGD/tumors), association with the main clinicopathological characteristics in terms of site of dysplastic lesion/tumor and stage of the tumor at the moment of blood draw have not been found ( P = 0.55; P = 0.50; respectively; Fig. 3 ). The stage at the moment of blood draw was considered cStage or pStage depending if blood draw has been performed at diagnosis or at surgery. Clinical endpoints (OS and PFS) were analyzed for the locally advanced/advanced EADC-EGJA group stratified by methylation status. A borderline difference in OS was observed, with hypomethylated cases that have a longer OS ( P = 0.05). The median OS of both categories was unreached. We did not find difference in PFS ( P = 0.49). The median PFS of normo-methylated category was 93.83 months and the one of hypomethylated was 28.06 (Supplementary Fig. 1). LINE-1 Methylation analysis in cell-free DNA (cfDNA) of longitudinal samples Twenty-six out of the 90 patients were studied longitudinally, including 11 NDBEs, 7 HGD/early EADC-EGJAs and 8 locally advanced/advanced EADC-EGJAs. All the 11 longitudinally followed NDBEs had a known clinical history of BE of at least 3 years. Nine out of the 11 NDBE patients were normo-methylated at the 1st blood draw: 7 of them showed similar methylation levels also in the longitudinally collected plasma samples, whereas 2 of them (B1 and B455) resulted hypomethylated at the first follow-up (Fig. 4 a). Patient B26 showed a borderline hypomethylation (93%) at the 1st blood draw and the level of methylation decreased further at the follow-up 2 years later (79.3%). The 1st cfDNA of patient B412 was hypomethylated, while the cfDNA collected at the next follow-up, more than three years later, resulted normo-methylated (Fig. 4 b). All the seven longitudinally studied HGD/early EADC-EGJA patients underwent an endoscopic or surgical treatment for the removal of the lesion such as radiofrequency ablation (RFA), mucosectomy (MS) or surgical resection. In three patients (B57, B277, G63) the cfDNA, collected at the time of lesion removal, was hypomethylated. Patients B57 and B277, which had BE histology after the treatment, had the cfDNA of this timepoint normo-methylated (Fig. 5 a). Patient G63 had the methylation of its cfDNA samples, collected at the 1st and 2nd follow-up after surgery and adjuvant therapy, just above the cut-off (Fig. 5 a). This patient had no evidence of disease (NED) after surgery. The other four patients (B603, G13, G34 and G62) who were normo-methylated at the surgery or diagnosis, kept almost unaltered their methylation level at their follow-ups several months after surgery. Interestingly, these patients had NED or turned and remained with BE histology after surgery (Fig. 5 b). The cfDNA sample, collected at surgery (baseline), of 3 out of the 8 longitudinally studied locally advanced/advanced EADC-EGJA patients was hypomethylated (Fig. 6 a). Of those three patients showing hypomethylation at the baseline, two (A168 and G18) had the cfDNA sample, collected at the 1st follow-up after esophagectomy, normo-methylated; whereas one (A90) still showed hypomethylation at this time-point (Fig. 6 a). Patient A168 maintained its cfDNA normo-methylated also at the 2nd follow-up, several months after surgery (Fig. 6 a) when the patient was found with NED. Patient G18 showed a decreased trend that remained in the range of normo-methylation at the 2nd follow-up 14 months after surgery, in accordance with NED status. However, more than a year after this point, this patient developed brain metastasis. Unfortunately, the blood draw at this point was not available. Patient A90 had progression with pulmonary metastasis after surgery. Chemotherapy was administered, leading to stable disease (SD) at the last follow-up (Fig. 6 a). Five out of the 8 longitudinally studied locally advanced/advanced EADC-EGJAs were normo-methylated since the time of the resection (Fig. 6 b). Two patients (A556 and G64) had a marked hypomethylation of their cfDNA collected at 10 and 6 months after surgery, respectively, in correspondence of brain metastasis (A556) or SD (G64). Patient G74 had a decrease of methylation level that remained in the range of normo-methylation (borderline) at the cfDNA collected at the 1st follow-up after surgery, in accordance to NED status. For G33 patient, we observed, at the timepoint corresponding to liver metastasis, a slightly decrease trend of methylation but still in the normal range. Unfortunately, an additional blood draw of a successive follow-up, during the adjuvant therapy, was not available to confirm this trend. Patient A564 had a stable normo-methylation despite the occurrence of pulmonary metastasis (Fig. 6 b). Discussion EADC-EGJA is a very aggressive cancer with poor prognosis, often preceded by BE, its metaplastic precursor. Histologically-defined grading determines the patient's management 8 . Several unmet clinical needs still exist, such as the identification of BE patients who are most at risk of progression and the identification of EADC-EGJA patients who are at risk of progression/recurrence. Molecular profiling has improved our understanding of the mutational processes underlying EADC-EGJA, however, how early these processes occur is not fully understood yet 41 , 49 , 50 . Epigenetic alterations are crucial event involved in the carcinogenesis process of different malignancies 17 , and among them, the global hypomethylation is linked with genetic instability and pro-carcinogenic mechanisms 19 . In this study, with the aim to investigate the changes in global methylation level during neoplastic progression of EADC-EGJA and to clarify if this biomarker could be studied to monitor the disease behavior, we analyzed a cohort of 90 cfDNA samples: 30 NDBEs, 30 HGD/early EADC-EGJAs and 30 locally advanced/advanced EADC-EGJAs; additionally, 26 of these patients were prospectively studied. To estimate global methylation, LINE-1 was used, as this biomarker is a well-known surrogate of this epigenetic event 22 . The data regarding LINE-1 methylation level in the 90 cfDNA samples suggested that global hypomethylation of DNA occurs more frequently in invasive EADC-EGJA compared to dysplasia and BE, however, this epigenetic event could be present also in these latter early conditions. The tendency to have a more frequent global hypomethylation in the locally advanced/advanced EADC-EGJA group suggested that this alteration could be considered part of the cascade of late dramatic events that drive dysplasia to invasive cancer. In literature, there are few data about global hypomethylation in EADC-EGJA 40 and, additionally, it is not always clear if data are referred to exclusively EADC-EGJA histology or if ESCC are included 51 . Moreover, there are no data about global hypomethylation in the EADC-EGJA carcinogenesis process from pre-neoplastic lesions to invasive carcinoma, while, more data exist in gastric cancer, showing a decreased methylation level moving from pre-neoplastic lesion toward cancer. Indeed, three studies have investigated LINE-1 methylation level in tissue samples of gastric cancer, using bisulfite conversion coupled with pyrosequencing 52 , 53 or digestion with restriction enzyme (COBRA LINE-1) 54 . The two studies conducted in Asiatic population are concordant in finding, since the HGD/adenoma carcinogenic step, a decrease in LINE-1 methylation level that remained hypomethylated in a stable manner in tumor. Hence, both studies suggest a rising of hypomethylation event in proximity to the neoplastic transformation, while in the preneoplastic stages (LGD and gastritis) hypomethylation is very rare 53 , 54 . The study conducted in Caucasian population, despite it did not investigate dysplasia stages as the two Asiatic studies, confirmed that hypomethylation event is a peculiar feature of gastric cancer rather than early preneoplastic stages such as gastritis 52 . In two of these three studies the authors investigated also the correlation of LINE-1 methylation level with age, finding a trend that did not reach significance in gastric cancer cohort in one study 52 and a significant inverse correlation in male individuals of the gastric cancer cohort in the other one 53 . In our study we did not find a correlation between LINE-1 methylation level and age in NDBEs, HGD/early EADC-EGJAs and locally advanced/advanced EADC-EGJAs also considering the three groups together. This result indicates that age is not a possible confounding factor for this biomarker in our population. Moreover, we did not find association with the main clinicopathological variables such as length of BE, site of dysplastic lesion/tumor and stage at the moment of blood draw. We found a borderline difference in OS time and no difference in PFS time in LINE-1 methylation level in locally advanced/advanced EADC-EGJA population. However, we are aware that any conclusion about these clinical endpoints has to be interpreted with caution because the locally advanced/advanced EADC-EGJAs, once dichotomized according to methylation level, was constituted by a small number of patients for each group (especially the hypomethylated one). Hence, the association between LINE-1 methylation level and clinical endpoint should be investigated in a larger cohort of EADC-EGJA with a reasonable number of both hypomethylated and normo-methylated tumors. To our knowledge there are no data in literature about LINE-1 methylation level and prognosis in EADC-EGJA, indeed, in EC, LINE-1 status has been principally investigated in ESCC, finding frequent hypomethylation associated with poorer survival 51 . Referring again to gastric cancer data, association between LINE-1 hypomethylation and OS is controversial, this discrepancy between studies could be also due to the different ethnicity of studied populations 52 , 53 , 55 , 56 . Hypomethylation has been associated to worse OS in certain tumor types including CRC, lung, and ovarian cancer 25 , 27 , 36 while it has been associated with a better OS in stage IIIC melanoma patients 57 , suggesting that hypomethylation effect on OS could be tumor-type specific. The overall decrease of methylation level (median methylation loss: 11%) observed in our study might seem small. However, even just a small change in global hypomethylation could have a potential huge effect on the cell, because the open chromatin could trigger the expression of oncogenes, the DNA could be more exposed to damaging agents and also transposable elements, such as LINE-1 itself, could retrotranspose and insert into genes, causing genome alterations 45 . Indeed, it was demonstrated that a peculiar class of structural variations is represented by mobile element insertions that occur as a consequence of the excision and re-insertion of repeated sequences such as LINE-1 and ALU. In particular, in EADC-EGJA, LINE-1 insertions have been reported in the coding sequence of several genes and mobile element activity represents the most relevant contributor to the total mutational burden in this type of tumor 41 – 44 . In our study we analyzed 26 longitudinal cases, following the LINE-1 methylation level in their sequential blood draws collected at each scheduled follow-up. Results from NDBE studied in longitudinal showed that the majority of patients maintained LINE-1 normo-methylation for years, confirming the rareness of LINE-1 event in preneoplastic lesion of the esophagus and its stability over time. Only in four cases (B1, B455, B26, and B412) we observed a more complex trend of LINE-1 methylation, that did not perfectly fit with the clinical history. For patient B412 whose cfDNA was hypomethylated at the enrollment and then normo-methylated at the successive blood draws, we hypothesized that hypomethylation may have been a passenger alteration. For the other three patients (B1, B455 and B26,), which showed hypomethylation of their last blood draw, it could be intriguing to keep them monitored to check if this phenomenon was a passenger alteration or if it predicted an evolution to dysplasia/adenocarcinoma. Regarding longitudinal HGD/early EADC-EGJA patients, the majority of them were normo-methylated at surgery and maintained this status during their whole clinical iter, suggesting again that hypomethylation event is quite rare in early lesions. However, for the few cases that showed hypomethylation at the time of surgery, LINE-1 turned to normo-methylation after the resection according to NED. The methylation level during the clinical history of six out of patients eight locally advanced/advanced EADC-EGJA longitudinal cases (A168, G18, A90, A556, G64 and G74), regardless of their methylation status at the baseline surgery point (hypomethylated or normo-methylated), perfectly fit with the clinical status. In particular, normal or altered level corresponded with NED or disease persistence/progression with metastasis, respectively. Interestingly, A556 and G64 had the baseline point normo-methylated, suggesting that hypomethylated clones may have developed later. For G33 patient, the decreased trend of methylation at 10 months after surgery, even if hypomethylation status was not reached, could explain the occurrence of liver metastasis. However, the lack of other blood draws during the adjuvant therapy to confirm this trend is a limitation for this case. For A564 patient the methylation level did not fit the clinical status, probably because changes in methylation did not contribute to the carcinogenesis of the tumor, neither at the time of progression with metastasis. Considering data from longitudinal studies altogether, it emerged that LINE-1 was normo-methylated in the majority of NDBE, while in early EADC-EGJA/HGD and locally advanced/advanced EADC-EGJA, LINE-1 was more frequently altered and it is a promising marker to monitor the persistence of molecular residual disease (MRD)/molecular relapse (MR). Since patients with advanced adenocarcinoma of the esophagus who undergo curative surgery often develop recurrent disease, finding a biomarker that could predict the postsurgical diagnosis of MRD/MR is of great interest, indeed, MRD/MR detection assays had the potential utility to allow personalization of adjuvant therapy 58 . The possibility to use LINE-1 methylation level in cfDNA as a measure of MRD after surgery has been investigated in a previous study conducted in a Japanese cohort of gastric cancer patients who underwent surgery. Authors found a correlation between post-surgical high concentrations of long-fragment LINE-1 and MRD but they did not find correlation with the methylation level 56 . Besides difference in ethnicity, the failure of this study to find a correlation with methylation level in post-surgery cfDNA could be explained by the usage of qPCR, which could be influenced by the decrease of tumor cfDNA amount after the resection of tumoral mass. In our opinion, ddPCR, due to the partitioning of the sample into droplets, that permit to dilute normal cfDNA background maximizing the chance of rare alterations detection, is superior in detecting small differences in methylation level in cfDNA, especially after the removal of tumor mass. A limitation of this work was that we did not enroll BE patients evolving to HGD or up to EADC-EGJA, although it would be appealing to study the trend of this biomarker in longitudinally collected blood draws of those patients. Unfortunately, we could not address this issue because BE progressors are very rare 8 . Another limit of this study was that we did not be able to have all information for all patients for additional risk factors, like smoking habit, which has been reported to increase the risk of EADC-EGJA in a dose responsive association, and obesity, which is associated not only with EADC-EGJA and BE but also with the development of dysplasia 59 – 62 . In conclusion, our study suggests that global hypomethylation occurs just prior to cancer invasiveness and could be a promising liquid biopsy biomarker to monitor the presence of residual disease or recurrence (MRD/MR) in HGD or locally advanced/ advanced EADC-EGJA patients which underwent endoscopic or surgical resection. Declarations Acknowledgements This work was supported by the following grants: RICERCA CORRENTE 2024, Italian Ministry of Health and Veneto Institute of Oncology IOV-IRCCS research program ESAMED (BIOV19BOLDRI). Author contributions Conceptualization: E.B.; Methodology: E.B., M.A.P. and A.V.; Software: E.B., M.A.P., A.V. and G.Ma.; Validation: E.B. and M.A.P. Formal analysis: E.B., M.A.P., A.V. and G.Ma.; Investigation: E.B., M.A.P. and A.V.; Resources: E.B., R.A., M.F., T.M., A.M., S.R., G.M., P.P. and A.F.; Data curation: E.B., M.A.P., A.V. and G.Ma.; Writing—original draft preparation: E.B., and M.A.P.; Writing—review & editing: E.B., M.A.P., A.V., R.A., M.F., T.M., A.M., S.R., G.M., G.Ma., A.R., P.P., A.F. and M.C.; Visualization: E.B., M.A.P. and G.Ma.; Supervision: E.B., M.A.P., A.R., P.P., A.F. and M.C.; Project administration: E.B. and A.R.; Funding acquisition: E.B. and A.R. All authors have read, reviewed and agreed to the published version of the manuscript. Competing interests The authors declare no competing interests. Data availability Data and materials supporting the conclusion of this article are included within the text, tables and figures. 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Role of body composition and metabolic profile in Barrett’s oesophagus and progression to cancer. Eur J Gastroenterol Hepatol 28 , 251–260 (2016). Additional Declarations No competing interests reported. Supplementary Files SupplementaryFig.1.jpg Supplementary Fig. 1 Overall survival and progression-free survival of locally advanced/advanced EADC-EGJA. Normo-methylated and hypomethylated OS curves are shown in solid and dashed lines, respectively. EADC-EGJA: esophageal adenocarcinoma-esophageal junction adenocarcinoma. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5348931","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":381408585,"identity":"37d70e2a-a923-4fd1-b36b-e542a20250de","order_by":0,"name":"Elisa 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The cut-off of 93.06% below which the sample was considered as hypomethylated is shown in dashed line. \u003cstrong\u003eb) \u003c/strong\u003eDistribution of hypomethylated and normo-methylated for each group\u003cstrong\u003e.\u003c/strong\u003e NDBE: never dysplastic Barrett; HGD: high-grade dysplasia; EADC-EGJA: esophageal adenocarcinoma-esophageal junction adenocarcinoma; ns: not significant; *\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05. LINE-1: Long interspersed nuclear element-1; NDBE: never dysplastic Barrett, HGD: high-grade dysplasia; EADC-EGJA: esophageal adenocarcinoma-esophageal junction adenocarcinoma.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5348931/v1/7a6866f32b0e42702d0b8079.jpg"},{"id":70926476,"identity":"9620ccf8-292b-44a9-bf36-d06b4f87a7d4","added_by":"auto","created_at":"2024-12-09 09:11:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1223603,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation between LINE-1 methylation and age in cfDNAs of NDBEs, HGD/early EADC-EGJAs, locally advanced/advanced EADC-EGJAs, in all patients considered together and in healthy controls.\u003c/strong\u003e LINE-1: Long interspersed nuclear element-1; NDBE: never dysplastic Barrett; HGD: high-grade dysplasia; EADC-EGJA: esophageal adenocarcinoma-esophageal junction adenocarcinoma.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5348931/v1/659ea7689884e2ec2e86f94b.jpg"},{"id":70926900,"identity":"298a1942-e43b-43a8-9a2e-1762b221b7cd","added_by":"auto","created_at":"2024-12-09 09:19:52","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1625335,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDot plot of LINE-1 methylation level according to the different clinicopathological characteristics.\u003c/strong\u003eLINE-1: Long interspersed nuclear element-1; NDBE: never dysplastic Barrett; BE: Barrett’s esophagus; HGD: high-grade dysplasia.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5348931/v1/783560d78e006e8d7eebfc00.jpg"},{"id":70924557,"identity":"aae62c1b-90cd-4fe9-b5aa-8261f482a925","added_by":"auto","created_at":"2024-12-09 09:03:52","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2155897,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLINE-1 methylation level in longitudinal cfDNA samples of NDBEs.\u003c/strong\u003e Patients showing normo-methylation \u003cstrong\u003ea)\u003c/strong\u003e or hypomethylation \u003cstrong\u003eb)\u003c/strong\u003eat the baseline. LINE-1: Long interspersed nuclear element-1; BE: Barrett’s esophagus. Timepoint ”0” (baseline) identifies the time of enrollment.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5348931/v1/7f23db49d9374dc9a98335c2.jpg"},{"id":70923734,"identity":"dff9e074-2ea4-4647-b8fa-c1adbe136f22","added_by":"auto","created_at":"2024-12-09 08:55:52","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1673181,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLINE-1 methylation level in longitudinal cfDNA samples of HGD/early EADC-EGJAs.\u003c/strong\u003e Patients showing hypomethylation \u003cstrong\u003ea)\u003c/strong\u003e or normo-methylation \u003cstrong\u003eb)\u003c/strong\u003e at the baseline. LINE-1: Long interspersed nuclear element-1; HGD: high-grade dysplasia; EADC: esophageal adenocarcinoma; EGJA: esophageal junction adenocarcinoma; BE: Barrett’s esophagus; MS: mucosectomy; RFA: radiofrequency ablation; NED: no evidence of disease; neo: neoadjuvant therapy; adjuv: adjuvant therapy. Timepoint ”0” (baseline) identifies the time of diagnosis or treatment (MS, RFA or surgery).\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5348931/v1/cd346ca7dda690e7d9fdd96f.jpg"},{"id":70924555,"identity":"92a6bb64-1ef8-4b38-b292-e9695f49a797","added_by":"auto","created_at":"2024-12-09 09:03:52","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1963966,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLINE-1 methylation level in longitudinal cfDNA samples of locally advanced/advanced EADC-EGJAs.\u003c/strong\u003ePatients showing hypomethylation (A) or normo-methylation (B) at the baseline. LINE-1: Long interspersed nuclear element-1; EGJA: esophageal junction adenocarcinoma; neo: neoadjuvant therapy; adjuv: adjuvant therapy; NED: no evidence of disease; SD: stable disease. Timepoint ”0” (baseline) identifies the time of surgery.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5348931/v1/e86bab8f7d27a36cb07c6218.jpg"},{"id":72953071,"identity":"9f2f15f4-4d59-41c4-8ead-b5f26e9a79cc","added_by":"auto","created_at":"2025-01-04 09:46:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10211539,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5348931/v1/4c5a1c5b-0522-4524-bbbe-13bd3c3a647c.pdf"},{"id":70923740,"identity":"8da2ebe2-57f0-4dda-910e-e91eddb804b2","added_by":"auto","created_at":"2024-12-09 08:55:52","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1822161,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Fig. 1 Overall survival and progression-free survival of locally advanced/advanced EADC-EGJA.\u003c/strong\u003e Normo-methylated and hypomethylated OS curves are shown in solid and dashed lines, respectively. EADC-EGJA: esophageal adenocarcinoma-esophageal junction adenocarcinoma.\u003c/p\u003e","description":"","filename":"SupplementaryFig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5348931/v1/94dcac1ad0c430623f110285.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Global hypomethylation as an MRD biomarker in esophageal and esophagogastric junction adenocarcinoma ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEsophageal cancer (EC) is the 8th most commonly diagnosed cancer and the 6th most common cause of cancer death in the world \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In Europe, in 2020, EC accounted for about 52,993 new diagnoses and 45,551 deaths \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Although its burden varies greatly across countries and populations, due to differences in the prevalence of underlying risk factors, survival from EC remains low, in the range of 10\u0026ndash;30% at 5 years post diagnosis in most countries \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEsophageal adenocarcinoma (EADC), the most frequent histotype of EC, occurs preferentially in the distal part of the esophagus, next to the junction with the stomach.\u003c/p\u003e \u003cp\u003eAge, gender (male), smoking habit, persistent gastro-esophageal reflux disease (GERD) and obesity are all risk factors for EADC development \u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe 8th edition of American Joint Committee on Cancer (AJCC) includes also the esophagogastric junction adenocarcinoma (EGJA) as EC when the tumor involves the junction and its epicenter is within the proximal 2 cm of the cardia \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAt the histological level, it is recognized that Barrett\u0026rsquo;s esophagus (BE) is a risk condition for EADC and EGJA, indeed, the majority of EADC and EGJA cases arise in an area of BE \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBE is characterized by the substitution of normal esophageal epithelium with columnar epithelium. One of the major causes of this transformation is attributed to inflammation and cell proliferation induced by the chronic exposure of lower esophagus to acid and bile salts typical of GERD \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Indeed, BE prevalence is higher in the population with GERD (7.7%) compared with population without this condition (\u0026lt;\u0026thinsp;5%) \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBE could evolve to low-grade (LGD), high-grade dysplasia (HGD) and finally invasive EADC \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The risk of progression of BE to EADC is around 0.3% per year in absence of dysplasia, but the risk rises to 5\u0026ndash;20% in presence of HGD \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. These observations led to the activation of surveillance protocols based on repetitive endoscopies together with targeted biopsies of the suspected areas followed by random biopsy sampling of the entire BE segment \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFrequency of surveillance endoscopy is determined by the detection of dysplasia. However, the efficacy of current surveillance protocols is still a matter of debate, and there is a great need to find biomarkers that could help to identify those BE patients at risk of developing EADC, in order to better tailor their follow-up \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMoreover, there is still no consensus on indicators of EADC early detection, neither on monitoring of the duration of therapy response nor on early detection of progression/recurrence yet.\u003c/p\u003e \u003cp\u003eAt the molecular level, according to the multi-step model of progression, dysplasia evolves to invasive EADC via the progressive accumulation of mutations and somatic copy number alterations (SCNAs) in tumor suppressor genes and oncogenes \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eStudies conducted by Next-generation sequencing (NGS) technologies revealed that also in never dysplastic Barrett\u0026rsquo;s esophagus (NDBE) are already present genetic alterations typical of EADC, suggesting that progression could be non-linear. These findings challenge the traditional multi-step model of progression to EADC \u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, and suggest that this progression is associated with a relatively small number of additional mutations or that other events are crucial to further promote the late step of carcinogenesis \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIt has been proposed that one of the mechanisms that promote the rapid progression of preneoplastic lesions to invasive EADC is the occurrence of genomic catastrophes such as chromothripsis, repeated breakage\u0026ndash;fusion\u0026ndash;bridge cycles and whole-genome doubling (WGD)\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGrowing evidence supports the hypothesis that epigenetic alterations can contribute to the acquisition of cancer hallmark capabilities during tumor development and malignant progression\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Among the possible epigenetic events, alteration of methylation level, primarily in the form of tumor suppressor gene hypermethylation, has been frequently found in EADC and NDBE \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGenome-wide methylation analysis conducted in a variety of cancers has revealed that, next to a selective hypermethylation at the CpG islands of specific tumor suppressor gene promoters, the dominant epigenetic change is global hypomethylation \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe Long-Interspersed Element-1 (LINE-1), since it constitutes a consistent part of the human genome (17%), has been indicated as a possible surrogate marker of global methylation status\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eLINE-1 methylation analysis has been conducted in many of the most common lethal cancers, and has been often associated with a poor outcome \u003csup\u003e\u003cspan additionalcitationids=\"CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33 CR34 CR35\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn EC, LINE-1 status has been principally investigated in squamous cell carcinoma (ESCC), the other main EC histotype, in which its hypomethylation is frequent and associated with poorer survival \u003csup\u003e\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. In EADC there are less data, however, we have previously demonstrated that LINE-1 is frequently hypomethylated both in solid and liquid biopsies of EADC patients compared to the constitutive genomic DNA isolated from peripheral blood mononuclear cells (PBMCs) \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Other studies supported the occurrence of LINE-1 hypomethylation in EADC, such as the demonstration that its retrotransposition is active and contributes to its genomic instability through insertions in the coding sequence of several genes (\u003cem\u003eERBB4\u003c/em\u003e, \u003cem\u003eCTNNA3\u003c/em\u003e, \u003cem\u003eCTNNA2\u003c/em\u003e, \u003cem\u003eCDH18\u003c/em\u003e, and \u003cem\u003eSOX5\u003c/em\u003e) \u003csup\u003e\u003cspan additionalcitationids=\"CR42 CR43\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Indeed, the retrotransposition of LINE-1 in cancer cells seems to be associated with its aberrant hypomethylation during carcinogenesis, while, in physiological conditions, retrotransposition is inhibited by hypermethylation of this element\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDue to these promising results in EADC, in this work, in order to define whether LINE-1 methylation level is affected during the carcinogenesis process, beside a cohort of 30 locally advanced/advanced EADC-EGJA patients, we extended the analysis, in liquid biopsy, of LINE-1 methylation status to HGD/early EADC-EGJA and to BE.\u003c/p\u003e \u003cp\u003eMoreover, to define if this biomarker could predict the patient clinical outcome, for several individuals we included a longitudinal monitoring through repetitive cfDNA sampling.\u003c/p\u003e \u003cp\u003eConsidering the possibility to have a lower amount of cfDNA in the bloodstream of patients with pre-neoplastic lesions in comparison with those affected by tumor, the use of a sensitive molecular approach to improve LINE-1 methylation detection in liquid biopsy should be considered. To address this purpose, we choose droplet digital PCR (ddPCR) technology, which is an endpoint method for precise and absolute quantification of nucleic acids \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. This feature, together with the partitioning of the sample in thousands of individual PCR reaction, offers the advantage of direct and accurate quantification of template, maximizing the chance to detect rare genetic alterations \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. To discriminate methylated and unmethylated cytosines within CpG islands in LINE-1 promoter, a particular type of ddPCR called Methylation-Sensitive Restriction Enzyme ddPCR (MSRE-ddPCR) was used.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eIn this prospective study, a total of 90 patients, 30 diagnosed with NDBE, 30 with HGD or early EADC-EGJA, and 30 with locally advanced/advanced EADC-EGJA have been included.\u003c/p\u003e \u003cp\u003eNDBE were defined as BE patients with a clinical history of stable disease for at least 3 years (range: 3\u0026ndash;12 years; median: 5 years). For NDBE patients, the length of the Barrett\u0026rsquo;s lesion defined the patient as \u0026ldquo;long\u0026rdquo; or \u0026ldquo;short\u0026rdquo; NDBE.\u003c/p\u003e \u003cp\u003eAll the enrolled patients were recruited from the Gastroenterology Unit and/or from the Surgical Oncology of Digestive Tract Unit of Veneto Institute of Oncology IOV \u0026ndash; IRCCS (Padua, Italy) between July 2014 and June 2023. Inclusion criteria were: i) age\u0026thinsp;\u0026gt;\u0026thinsp;18 years; ii) histological diagnosis of BE, HGD/early EADC-EGJA or locally advanced/advanced EADC-EGJA. Concurrent diagnosis of synchronous or metachronous tumor within 5 years was an exclusion criterium. For each patient, a blood sample was collected at different time points: at the enrollment for NDBEs, at the diagnosis/surgery for HGD/early EADC-EGJAs, and at the diagnosis/surgery for locally advanced/advanced EADC-EGJAs. Twenty-six of the 90 patients were also longitudinally studied including 11 NDBE, 7 HDG/early EADC-EGJA and 8 locally advanced/advanced EADC-EGJA patients. For these cases, at least two blood samples in different follow-up were collected. Blood samples of 20 healthy volunteers (median age: 30.5 years; range: 21\u0026ndash;65 years; males: 8, females: 12) were also included. The present study was approved by the IOV-IRCCS Comitato Etico per la Sperimentazione Clinica (CESC) (cod. number CESC IOV: 2020/125) and carried out in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki and its later amendments). All the patients involved in this study expressed their written consensus to blood sampling and data treatment in accordance with the Helsinki Declaration.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDNA extraction\u003c/h3\u003e\n\u003cp\u003ePeripheral blood samples were collected in cell-free DNA BCT tubes (Streck). Plasma was isolated as described in \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. One aliquot of whole blood was also stored for germline DNA (gDNA) extraction. cfDNA was extracted from 1 ml of plasma using Maxwell RSC cfDNA Plasma Kit (Promega). gDNA was isolated from 500 \u0026micro;l of peripheral blood with Maxwell RSC Whole Blood DNA Kit (Promega). cfDNA and gDNA quantity were assessed with Qubit dsDNA HS Assay kit (Thermo Fisher Scientific). Quality of randomly selected cfDNA samples was evaluated by Agilent TapeStation 2200 using Cell-free DNA Screen Tape Assay kit (Agilent Technologies).\u003c/p\u003e\n\u003ch3\u003eMethylation-Sensitive Restriction Enzyme droplet digital PCR (MSRE-ddPCR)\u003c/h3\u003e\n\u003cp\u003eLINE-1 methylation was analyzed by a MSRE-ddPCR in-house designed assay.\u003c/p\u003e \u003cp\u003egDNA and cfDNA of each patient were digested or not digested with HpaII (New England BioLabs), a methylation-sensitive enzyme that cuts CCGG recognition site when both cytosines are unmethylated and, with a lower efficiency, when the external cytosine is methylated (mCCGG); while it is inhibited when both cytosines are methylated (mCmCGG).\u003c/p\u003e \u003cp\u003eDigested and undigested DNA have been amplified by ddPCR with primers for the amplification of a sequence between nucleotides 12\u0026ndash;128 of LINE-1 promoter (GenBank accession number X58075.1). This region contains two CCGG sites.\u003c/p\u003e \u003cp\u003eTwo different ddPCR reaction mixes of 20 \u0026micro;l with or without HpaII were prepared. Reaction mixes contained 10 \u0026micro;L of 2\u0026times; ddPCR SuperMix for Probes (No dUTP) (Bio-Rad), 1 \u0026micro;L of 20\u0026times; target LINE-1 primers/probe (FAM), 1 \u0026micro;L (10 U) of HpaII (for digested sample) or 1 \u0026micro;L of H\u003csub\u003e2\u003c/sub\u003eO (for undigested sample).\u003c/p\u003e \u003cp\u003eThe pair of primer/probe was in a final concentration of 900 nM/250 nM. Primer sequences were: 5\u0026prime; -CAAGATGGCCGAATAGGAAC (FW) and 5\u0026prime; -TGGCACTCCCTAGTGAGATG (RW). A DNA input of 0.01 ng/well was used as template. Each ddPCR included, as positive and negative controls, a Human WGA Methylated DNA and Human WGA Non-methylated DNA (Zymo Research). No-template control was included. Droplets were generated by QX200 droplet generator (Bio-Rad). An Applied Biosystems VeritiDx thermal cycler was used to perform first enzymatic digestion reaction at 37\u0026deg;C for 2 hours and, subsequently, enzyme inactivation at 95\u0026deg;C for 20\u0026rsquo;, followed by PCR amplification using these conditions: 95\u0026deg;C for 10\u0026prime;, followed by 50 cycles at 94\u0026deg;C for 30\u0026Prime;, 60\u0026deg;C for 1\u0026prime;, and 98\u0026deg;C for 10\u0026prime;. Each reaction was performed in two replicates.\u003c/p\u003e \u003cp\u003eDroplets were read with QX200 droplet reader and analyzed with QuantaSoft\u0026trade; version 1.7.4 (Bio-Rad). Positive droplets, containing amplification products, were discriminated from negative ones by applying a fluorescence amplitude threshold that was set manually. The software quantified the number of copies/\u0026micro;L for each well as output. The mean of two replicates was calculated to obtain a more accurate value. Samples with \u0026lt;\u0026thinsp;10,000 droplets per 20 \u0026micro;L of PCR reaction were excluded from analysis.\u003c/p\u003e \u003cp\u003eThe methylation level in the cfDNA sample of a patient, using lymphocytes-derived gDNA as reference, was calculated by this formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\mathbf{c}\\mathbf{f}\\mathbf{D}\\mathbf{N}\\mathbf{A}\\:\\mathbf{m}\\mathbf{e}\\mathbf{t}\\mathbf{h}\\mathbf{y}\\mathbf{l}\\mathbf{a}\\mathbf{t}\\mathbf{i}\\mathbf{o}\\mathbf{n}\\:\\left(\\mathbf{\\%}\\right)=\\frac{\\mathbf{n}^\\circ\\:\\:\\mathbf{c}\\mathbf{o}\\mathbf{p}\\mathbf{i}\\mathbf{e}\\mathbf{s}/\\varvec{\\mu\\:}\\mathbf{L}\\:\\left(\\mathbf{d}\\mathbf{i}\\mathbf{g}\\mathbf{e}\\mathbf{s}\\mathbf{t}\\mathbf{e}\\mathbf{d}\\:\\mathbf{c}\\mathbf{f}\\mathbf{D}\\mathbf{N}\\mathbf{A}\\right)\\:)/\\mathbf{n}^\\circ\\:\\:\\mathbf{c}\\mathbf{o}\\mathbf{p}\\mathbf{i}\\mathbf{e}\\mathbf{s}/\\varvec{\\mu\\:}\\mathbf{L}(\\mathbf{u}\\mathbf{n}\\mathbf{d}\\mathbf{i}\\mathbf{g}\\mathbf{e}\\mathbf{s}\\mathbf{t}\\mathbf{e}\\mathbf{d}\\:\\mathbf{c}\\mathbf{f}\\mathbf{D}\\mathbf{N}\\mathbf{A})\\:}{\\mathbf{n}^\\circ\\:\\:\\mathbf{c}\\mathbf{o}\\mathbf{p}\\mathbf{i}\\mathbf{e}\\mathbf{s}/\\varvec{\\mu\\:}\\mathbf{L}\\left(\\mathbf{d}\\mathbf{i}\\mathbf{g}\\mathbf{e}\\mathbf{s}\\mathbf{t}\\mathbf{e}\\mathbf{d}\\:\\mathbf{g}\\mathbf{D}\\mathbf{N}\\mathbf{A}\\right)\\:)/\\mathbf{n}^\\circ\\:\\:\\mathbf{c}\\mathbf{o}\\mathbf{p}\\mathbf{i}\\mathbf{e}\\mathbf{s}/\\varvec{\\mu\\:}\\mathbf{L}(\\mathbf{u}\\mathbf{n}\\mathbf{d}\\mathbf{i}\\mathbf{g}\\mathbf{e}\\mathbf{s}\\mathbf{t}\\mathbf{e}\\mathbf{d}\\:\\mathbf{g}\\mathbf{D}\\mathbf{N}\\mathbf{A})\\:}\\varvec{x}\\:100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eTo set up the cut-off value to consider a cfDNA as hypomethylated, we carried out the same procedure as the test samples by analyzing cfDNA and gDNA of 20 healthy volunteers. The established cut-off value, under which the test sample has been considered hypomethylated, was determined as the mean of the % methylation level of cfDNA \u0026minus;\u0026thinsp;2SD (98.67% \u0026minus;\u0026thinsp;2SD\u0026thinsp;=\u0026thinsp;93.06%).\u003c/p\u003e\n\u003ch3\u003eStatistics\u003c/h3\u003e\n\u003cp\u003eDifferences in distribution between groups for categorical variables were evaluated using chi-squared or Fisher\u0026rsquo;s exact test. Differences in distribution between groups for continuous variables were evaluated using Mann-Whitney or Kruskal-Wallis test. Correlation analysis was performed using Spearman\u0026rsquo;s test. Overall survival (OS) was defined as the time between the date of tumor resection and the date of death for any cause or the date of the end of study (January 2024). Progression-free survival (PFS) was calculated as the time from the date of tumor resection to the date of progression, or the date of the end of the study. OS and PFS curves were defined using Kaplan-Meier function, differences between strata were estimated using log-rank test. Tests with \u003cem\u003eP\u003c/em\u003e values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant. Statistical analyses were performed using SigmaPlot version 14.0 (Systat Software Inc.). Graphs were generated using GraphPad Prism software (version 9.2 for Windows, San Diego, CA, USA).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eClinicopathological characteristics of patients\u003c/h2\u003e \u003cp\u003eThe clinicopathological characteristics of NDBE, HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA patients are reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe median age is slightly lower in NDBE patients compared with HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA (54.5; 68 and 66; respectively). The male/female ratio is similar in the three cohorts with a prevalence of males. The majority of NDBE were long BE with the lesion located at the esophagus, HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA have the lesion/tumor located in the esophagus or esophageal junction. cStage and pStage were reported according to Rice et al. \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOnly locally advanced/advanced EADC-EGJA received neoadjuvant treatment in almost all cases and received adjuvant therapy in case of pathological residual disease and suitability to receive the therapy.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinicopathological characteristics of NDBE, HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNDBE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHGD/early EADC-EGJA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLocally adv./\u003c/p\u003e \u003cp\u003eadv. EADC-EGJA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.5 (21\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68 (36\u0026ndash;86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66 (41\u0026ndash;87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIQR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27 (90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26 (86.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of BE lesion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eShort (\u0026lt;\u0026thinsp;3 cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (16.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLong (\u0026ge;\u0026thinsp;3 cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (83.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor site of lesion/tumor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEsophagus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26 (86.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (20%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEsophageal junction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (13.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24 (80%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ecStage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22 (73.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIVB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epStage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIIB-IIIB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16 (53.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown (no surgery)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (20%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeoadjuvant treatment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29 (96.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjuvant treatment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12 (40%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18 (60%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eNDBE: Never dysplastic Barrett; HGD: high-grade dysplasia; EADC: esophageal adenocarcinoma; EGJA: esophagogastric junction adenocarcinoma; IQR: interquartile range; BE: Barrett\u0026rsquo;s esophagus; cStage: clinical tumor stage; pStage: pathological tumor stage.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLINE-1 Methylation analysis in cell-free DNA at baseline\u003c/h3\u003e\n\u003cp\u003eLINE-1 methylation level was analyzed by MSRE-ddPCR in all patients. A cfDNA sample was considered hypomethylated when its residual methylation level was below to the cut-off level of 93.06%, calculated by analyzing the cfDNA and the gDNA of 20 healthy volunteers. The distribution of the methylation level of the cfDNA samples in the three groups of patients is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThree out of 30 (10%), 6 out of 30 (20%) and 10 out of 30 (33.3%) cfDNAs resulted hypomethylated in NDBE, HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA groups, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Locally advanced/advanced EADC-EGJAs had a significantly higher number of hypomethylated samples compared to NDBEs (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb), whereas the difference in the frequency of hypomethylated cfDNA samples was not significant between NDBEs and HGD/early EADC-EGJAs and between HGD/early EADC-EGJAs and locally advanced/advanced EADC-EGJAs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eThe overall decrease of methylation level, considering all the hypomethylated samples of the three groups together, ranged from 7.6\u0026ndash;20.8%, with a median of 11% (IQR\u0026thinsp;=\u0026thinsp;5.9%).\u003c/p\u003e \u003cp\u003eAssociation between LINE-1 methylation level and the clinicopathological characteristics of patients has been investigated. A correlation between LINE-1 methylation values and age in all patients considered together and divided by the three groups was not observed (r\u0026thinsp;=\u0026thinsp;0.037, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.727 for all patients; r\u0026thinsp;=\u0026thinsp;0.073, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.701 for NDBE; r = -0.078, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.682 for HGD/early EADC-EGJA; r\u0026thinsp;=\u0026thinsp;0.115, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.546 for locally advanced/advanced EADC-EGJA). No correlation was observed for healthy controls either (r = -0.191, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.419) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAssociation between methylation level and gender in all patients has been not observed (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.112; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eConcerning the preneoplastic lesion group (NDBE), association with the length of BE has not been found (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.69; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Moreover, in the two groups of neoplastic lesions (HGD/tumors), association with the main clinicopathological characteristics in terms of site of dysplastic lesion/tumor and stage of the tumor at the moment of blood draw have not been found (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.55; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.50; respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The stage at the moment of blood draw was considered cStage or pStage depending if blood draw has been performed at diagnosis or at surgery.\u003c/p\u003e \u003cp\u003eClinical endpoints (OS and PFS) were analyzed for the locally advanced/advanced EADC-EGJA group stratified by methylation status. A borderline difference in OS was observed, with hypomethylated cases that have a longer OS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05). The median OS of both categories was unreached. We did not find difference in PFS (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.49). The median PFS of normo-methylated category was 93.83 months and the one of hypomethylated was 28.06 (Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eLINE-1 Methylation analysis in cell-free DNA (cfDNA) of longitudinal samples\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTwenty-six out of the 90 patients were studied longitudinally, including 11 NDBEs, 7 HGD/early EADC-EGJAs and 8 locally advanced/advanced EADC-EGJAs.\u003c/p\u003e \u003cp\u003eAll the 11 longitudinally followed NDBEs had a known clinical history of BE of at least 3 years.\u003c/p\u003e \u003cp\u003eNine out of the 11 NDBE patients were normo-methylated at the 1st blood draw: 7 of them showed similar methylation levels also in the longitudinally collected plasma samples, whereas 2 of them (B1 and B455) resulted hypomethylated at the first follow-up (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ePatient B26 showed a borderline hypomethylation (93%) at the 1st blood draw and the level of methylation decreased further at the follow-up 2 years later (79.3%).\u003c/p\u003e \u003cp\u003eThe 1st cfDNA of patient B412 was hypomethylated, while the cfDNA collected at the next follow-up, more than three years later, resulted normo-methylated (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eAll the seven longitudinally studied HGD/early EADC-EGJA patients underwent an endoscopic or surgical treatment for the removal of the lesion such as radiofrequency ablation (RFA), mucosectomy (MS) or surgical resection. In three patients (B57, B277, G63) the cfDNA, collected at the time of lesion removal, was hypomethylated. Patients B57 and B277, which had BE histology after the treatment, had the cfDNA of this timepoint normo-methylated (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Patient G63 had the methylation of its cfDNA samples, collected at the 1st and 2nd follow-up after surgery and adjuvant therapy, just above the cut-off (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). This patient had no evidence of disease (NED) after surgery.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe other four patients (B603, G13, G34 and G62) who were normo-methylated at the surgery or diagnosis, kept almost unaltered their methylation level at their follow-ups several months after surgery. Interestingly, these patients had NED or turned and remained with BE histology after surgery (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eThe cfDNA sample, collected at surgery (baseline), of 3 out of the 8 longitudinally studied locally advanced/advanced EADC-EGJA patients was hypomethylated (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). Of those three patients showing hypomethylation at the baseline, two (A168 and G18) had the cfDNA sample, collected at the 1st follow-up after esophagectomy, normo-methylated; whereas one (A90) still showed hypomethylation at this time-point (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003ePatient A168 maintained its cfDNA normo-methylated also at the 2nd follow-up, several months after surgery (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea) when the patient was found with NED.\u003c/p\u003e \u003cp\u003ePatient G18 showed a decreased trend that remained in the range of normo-methylation at the 2nd follow-up 14 months after surgery, in accordance with NED status. However, more than a year after this point, this patient developed brain metastasis. Unfortunately, the blood draw at this point was not available.\u003c/p\u003e \u003cp\u003ePatient A90 had progression with pulmonary metastasis after surgery. Chemotherapy was administered, leading to stable disease (SD) at the last follow-up (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFive out of the 8 longitudinally studied locally advanced/advanced EADC-EGJAs were normo-methylated since the time of the resection (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eTwo patients (A556 and G64) had a marked hypomethylation of their cfDNA collected at 10 and 6 months after surgery, respectively, in correspondence of brain metastasis (A556) or SD (G64).\u003c/p\u003e \u003cp\u003ePatient G74 had a decrease of methylation level that remained in the range of normo-methylation (borderline) at the cfDNA collected at the 1st follow-up after surgery, in accordance to NED status.\u003c/p\u003e \u003cp\u003eFor G33 patient, we observed, at the timepoint corresponding to liver metastasis, a slightly decrease trend of methylation but still in the normal range. Unfortunately, an additional blood draw of a successive follow-up, during the adjuvant therapy, was not available to confirm this trend.\u003c/p\u003e \u003cp\u003ePatient A564 had a stable normo-methylation despite the occurrence of pulmonary metastasis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eEADC-EGJA is a very aggressive cancer with poor prognosis, often preceded by BE, its metaplastic precursor.\u003c/p\u003e \u003cp\u003eHistologically-defined grading determines the patient's management \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSeveral unmet clinical needs still exist, such as the identification of BE patients who are most at risk of progression and the identification of EADC-EGJA patients who are at risk of progression/recurrence.\u003c/p\u003e \u003cp\u003eMolecular profiling has improved our understanding of the mutational processes underlying EADC-EGJA, however, how early these processes occur is not fully understood yet \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEpigenetic alterations are crucial event involved in the carcinogenesis process of different malignancies \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, and among them, the global hypomethylation is linked with genetic instability and pro-carcinogenic mechanisms \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, with the aim to investigate the changes in global methylation level during neoplastic progression of EADC-EGJA and to clarify if this biomarker could be studied to monitor the disease behavior, we analyzed a cohort of 90 cfDNA samples: 30 NDBEs, 30 HGD/early EADC-EGJAs and 30 locally advanced/advanced EADC-EGJAs; additionally, 26 of these patients were prospectively studied.\u003c/p\u003e \u003cp\u003eTo estimate global methylation, LINE-1 was used, as this biomarker is a well-known surrogate of this epigenetic event \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe data regarding LINE-1 methylation level in the 90 cfDNA samples suggested that global hypomethylation of DNA occurs more frequently in invasive EADC-EGJA compared to dysplasia and BE, however, this epigenetic event could be present also in these latter early conditions.\u003c/p\u003e \u003cp\u003eThe tendency to have a more frequent global hypomethylation in the locally advanced/advanced EADC-EGJA group suggested that this alteration could be considered part of the cascade of late dramatic events that drive dysplasia to invasive cancer. In literature, there are few data about global hypomethylation in EADC-EGJA \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e and, additionally, it is not always clear if data are referred to exclusively EADC-EGJA histology or if ESCC are included \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMoreover, there are no data about global hypomethylation in the EADC-EGJA carcinogenesis process from pre-neoplastic lesions to invasive carcinoma, while, more data exist in gastric cancer, showing a decreased methylation level moving from pre-neoplastic lesion toward cancer. Indeed, three studies have investigated LINE-1 methylation level in tissue samples of gastric cancer, using bisulfite conversion coupled with pyrosequencing \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e or digestion with restriction enzyme (COBRA LINE-1) \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. The two studies conducted in Asiatic population are concordant in finding, since the HGD/adenoma carcinogenic step, a decrease in LINE-1 methylation level that remained hypomethylated in a stable manner in tumor. Hence, both studies suggest a rising of hypomethylation event in proximity to the neoplastic transformation, while in the preneoplastic stages (LGD and gastritis) hypomethylation is very rare \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe study conducted in Caucasian population, despite it did not investigate dysplasia stages as the two Asiatic studies, confirmed that hypomethylation event is a peculiar feature of gastric cancer rather than early preneoplastic stages such as gastritis \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn two of these three studies the authors investigated also the correlation of LINE-1 methylation level with age, finding a trend that did not reach significance in gastric cancer cohort in one study \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e and a significant inverse correlation in male individuals of the gastric cancer cohort in the other one \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. In our study we did not find a correlation between LINE-1 methylation level and age in NDBEs, HGD/early EADC-EGJAs and locally advanced/advanced EADC-EGJAs also considering the three groups together. This result indicates that age is not a possible confounding factor for this biomarker in our population. Moreover, we did not find association with the main clinicopathological variables such as length of BE, site of dysplastic lesion/tumor and stage at the moment of blood draw.\u003c/p\u003e \u003cp\u003eWe found a borderline difference in OS time and no difference in PFS time in LINE-1 methylation level in locally advanced/advanced EADC-EGJA population. However, we are aware that any conclusion about these clinical endpoints has to be interpreted with caution because the locally advanced/advanced EADC-EGJAs, once dichotomized according to methylation level, was constituted by a small number of patients for each group (especially the hypomethylated one). Hence, the association between LINE-1 methylation level and clinical endpoint should be investigated in a larger cohort of EADC-EGJA with a reasonable number of both hypomethylated and normo-methylated tumors.\u003c/p\u003e \u003cp\u003eTo our knowledge there are no data in literature about LINE-1 methylation level and prognosis in EADC-EGJA, indeed, in EC, LINE-1 status has been principally investigated in ESCC, finding frequent hypomethylation associated with poorer survival \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eReferring again to gastric cancer data, association between LINE-1 hypomethylation and OS is controversial, this discrepancy between studies could be also due to the different ethnicity of studied populations \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Hypomethylation has been associated to worse OS in certain tumor types including CRC, lung, and ovarian cancer \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e while it has been associated with a better OS in stage IIIC melanoma patients \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, suggesting that hypomethylation effect on OS could be tumor-type specific.\u003c/p\u003e \u003cp\u003eThe overall decrease of methylation level (median methylation loss: 11%) observed in our study might seem small. However, even just a small change in global hypomethylation could have a potential huge effect on the cell, because the open chromatin could trigger the expression of oncogenes, the DNA could be more exposed to damaging agents and also transposable elements, such as LINE-1 itself, could retrotranspose and insert into genes, causing genome alterations \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Indeed, it was demonstrated that a peculiar class of structural variations is represented by mobile element insertions that occur as a consequence of the excision and re-insertion of repeated sequences such as LINE-1 and ALU. In particular, in EADC-EGJA, LINE-1 insertions have been reported in the coding sequence of several genes and mobile element activity represents the most relevant contributor to the total mutational burden in this type of tumor \u003csup\u003e\u003cspan additionalcitationids=\"CR42 CR43\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn our study we analyzed 26 longitudinal cases, following the LINE-1 methylation level in their sequential blood draws collected at each scheduled follow-up.\u003c/p\u003e \u003cp\u003eResults from NDBE studied in longitudinal showed that the majority of patients maintained LINE-1 normo-methylation for years, confirming the rareness of LINE-1 event in preneoplastic lesion of the esophagus and its stability over time.\u003c/p\u003e \u003cp\u003eOnly in four cases (B1, B455, B26, and B412) we observed a more complex trend of LINE-1 methylation, that did not perfectly fit with the clinical history. For patient B412 whose cfDNA was hypomethylated at the enrollment and then normo-methylated at the successive blood draws, we hypothesized that hypomethylation may have been a passenger alteration. For the other three patients (B1, B455 and B26,), which showed hypomethylation of their last blood draw, it could be intriguing to keep them monitored to check if this phenomenon was a passenger alteration or if it predicted an evolution to dysplasia/adenocarcinoma.\u003c/p\u003e \u003cp\u003eRegarding longitudinal HGD/early EADC-EGJA patients, the majority of them were normo-methylated at surgery and maintained this status during their whole clinical iter, suggesting again that hypomethylation event is quite rare in early lesions. However, for the few cases that showed hypomethylation at the time of surgery, LINE-1 turned to normo-methylation after the resection according to NED.\u003c/p\u003e \u003cp\u003eThe methylation level during the clinical history of six out of patients eight locally advanced/advanced EADC-EGJA longitudinal cases (A168, G18, A90, A556, G64 and G74), regardless of their methylation status at the baseline surgery point (hypomethylated or normo-methylated), perfectly fit with the clinical status. In particular, normal or altered level corresponded with NED or disease persistence/progression with metastasis, respectively.\u003c/p\u003e \u003cp\u003eInterestingly, A556 and G64 had the baseline point normo-methylated, suggesting that hypomethylated clones may have developed later.\u003c/p\u003e \u003cp\u003eFor G33 patient, the decreased trend of methylation at 10 months after surgery, even if hypomethylation status was not reached, could explain the occurrence of liver metastasis. However, the lack of other blood draws during the adjuvant therapy to confirm this trend is a limitation for this case.\u003c/p\u003e \u003cp\u003eFor A564 patient the methylation level did not fit the clinical status, probably because changes in methylation did not contribute to the carcinogenesis of the tumor, neither at the time of progression with metastasis.\u003c/p\u003e \u003cp\u003eConsidering data from longitudinal studies altogether, it emerged that LINE-1 was normo-methylated in the majority of NDBE, while in early EADC-EGJA/HGD and locally advanced/advanced EADC-EGJA, LINE-1 was more frequently altered and it is a promising marker to monitor the persistence of molecular residual disease (MRD)/molecular relapse (MR).\u003c/p\u003e \u003cp\u003eSince patients with advanced adenocarcinoma of the esophagus who undergo curative surgery often develop recurrent disease, finding a biomarker that could predict the postsurgical diagnosis of MRD/MR is of great interest, indeed, MRD/MR detection assays had the potential utility to allow personalization of adjuvant therapy \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe possibility to use LINE-1 methylation level in cfDNA as a measure of MRD after surgery has been investigated in a previous study conducted in a Japanese cohort of gastric cancer patients who underwent surgery. Authors found a correlation between post-surgical high concentrations of long-fragment LINE-1 and MRD but they did not find correlation with the methylation level \u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Besides difference in ethnicity, the failure of this study to find a correlation with methylation level in post-surgery cfDNA could be explained by the usage of qPCR, which could be influenced by the decrease of tumor cfDNA amount after the resection of tumoral mass. In our opinion, ddPCR, due to the partitioning of the sample into droplets, that permit to dilute normal cfDNA background maximizing the chance of rare alterations detection, is superior in detecting small differences in methylation level in cfDNA, especially after the removal of tumor mass.\u003c/p\u003e \u003cp\u003eA limitation of this work was that we did not enroll BE patients evolving to HGD or up to EADC-EGJA, although it would be appealing to study the trend of this biomarker in longitudinally collected blood draws of those patients. Unfortunately, we could not address this issue because BE progressors are very rare \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAnother limit of this study was that we did not be able to have all information for all patients for additional risk factors, like smoking habit, which has been reported to increase the risk of EADC-EGJA in a dose responsive association, and obesity, which is associated not only with EADC-EGJA and BE but also with the development of dysplasia \u003csup\u003e\u003cspan additionalcitationids=\"CR60 CR61\" citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn conclusion, our study suggests that global hypomethylation occurs just prior to cancer invasiveness and could be a promising liquid biopsy biomarker to monitor the presence of residual disease or recurrence (MRD/MR) in HGD or locally advanced/ advanced EADC-EGJA patients which underwent endoscopic or surgical resection.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the following grants: RICERCA CORRENTE 2024, Italian Ministry of Health and Veneto Institute of Oncology IOV-IRCCS research program ESAMED (BIOV19BOLDRI).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: E.B.; \u0026nbsp; Methodology: E.B., M.A.P. and A.V.; Software: E.B., M.A.P., A.V. and G.Ma.; Validation: E.B. and M.A.P. Formal analysis: E.B., M.A.P., A.V. and G.Ma.; Investigation: E.B., M.A.P. and A.V.; Resources: E.B., R.A., M.F., T.M., A.M., S.R., G.M., P.P. and A.F.; Data curation: E.B., M.A.P., A.V. and G.Ma.; Writing\u0026mdash;original draft preparation: E.B., and M.A.P.; Writing\u0026mdash;review \u0026amp; editing: E.B., M.A.P., A.V., R.A., M.F., T.M., A.M., S.R., G.M., G.Ma., A.R., P.P., A.F. and M.C.; Visualization: E.B., M.A.P. and G.Ma.; Supervision: E.B., M.A.P., A.R., P.P., A.F. and M.C.; Project administration: E.B. and A.R.; Funding acquisition: E.B. and A.R.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors have read, reviewed and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData and materials supporting the conclusion of this article are included within the text, tables and figures.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary information\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMorgan, E. \u003cem\u003eet al.\u003c/em\u003e The Global Landscape of Esophageal Squamous Cell Carcinoma and Esophageal Adenocarcinoma Incidence and Mortality in 2020 and Projections to 2040: New Estimates From GLOBOCAN 2020. \u003cem\u003eGastroenterology\u003c/em\u003e \u003cstrong\u003e163\u003c/strong\u003e, 649-658.e2 (2022).\u003c/li\u003e\n\u003cli\u003eLiu, C.-Q. \u003cem\u003eet al.\u003c/em\u003e Epidemiology of esophageal cancer in 2020 and projections to 2030 and 2040. \u003cem\u003eThorac Cancer\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 3\u0026ndash;11 (2023).\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Doherty, M. 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Long interspersed nuclear element-1 (LINE-1) is considered a surrogate marker of global methylation, an epigenetic event contributing to progression.\u003c/p\u003e \u003cp\u003ecfDNA of 90 patients with never dysplastic Barrett\u0026rsquo;s (NDBE), HGD/early EADC-EGJA or locally advanced/advanced EADC-EGJA have been analyzed for LINE-1 methylation, by Methylation-Sensitive Restriction Enzyme droplet digital PCR. Twenty-six patients have been longitudinally studied.\u003c/p\u003e \u003cp\u003eGlobal hypomethylation increased during carcinogenesis, with significant difference between locally advanced/advanced EADC-EGJAs and NDBEs (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028). Longitudinal cases confirmed rareness and stability over time of hypomethylation in NDBEs. The majority of HGD/early EADC-EGJA and locally advanced/advanced EADC-EGJA showed methylation dynamic after resection according to clinical status, suggesting that global hypomethylation occurs just prior to cancer invasiveness and it is a promising biomarker to monitor molecular residual disease/recurrence.\u003c/p\u003e","manuscriptTitle":"Global hypomethylation as an MRD biomarker in esophageal and esophagogastric junction adenocarcinoma ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-09 08:55:47","doi":"10.21203/rs.3.rs-5348931/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e789f899-7d23-4afb-b09c-30c6ea07997c","owner":[],"postedDate":"December 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-04T09:38:21+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-09 08:55:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5348931","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5348931","identity":"rs-5348931","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}